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Objectives: Chronic rhinosinusitis is one of the common diseases that cause morbidity and affects a person's quality of life. We tried to provide a more appropriate and effective approach to selecting patients for endoscopic sinus surgery. Methods: The study population is chronic rhinosinusitis children referred to the ear, nose, and throat clinic of two general hospitals in Tehran, Iran, who have previously undergone sufficient drug treatment and have not recovered. The Lund-Mackay score is calculated by examining the computed tomography (CT) scan. The Sino-nasal Outcome Test-22 (SNOT-22) questionnaire was provided to the patients before the operation, after the operation, and 3 and 6 months later in the clinic. Results: Before the operation, the most SNOT-22 score people were in the range of 40-59 points. The SNOT-22 score before the operation is significantly different from 3 and 6 months after the operation. The highest frequency of Lund-Mackay CT (LMCT) scan score was in the range of 18-23 points. The LMCT scan score did not show any significant relationship with the SNOT-22 score before surgery, 3 months, and 6 months after surgery. Sensitivity to aspirin had a significant relationship with SNOT-22 scores and the history of asthma and nasal polyps had a significant relationship with the preoperative LMCT scan score. Conclusions: The LMCT scan scoring system cannot be a good measure of chronic rhinosinusitis severity or the prognosis of patients after surgery. The SNOT-22 questionnaire can be used as a predictive tool to help the doctor and the patient in deciding to operate and the possibility of obtaining a relative recovery.

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Background: Given the dearth of extensive research comparing the Glasgow Coma Scale with the Rotterdam scoring system for predicting mortality in trauma patients, this study was conducted to determine which scale provides a more realistic prediction of mortality in trauma patients after three months. Materials and Methods: This observational study was performed at Kashani Hospital in Isfahan, Iran. Patients with TBI who were admitted between February 2022 and February 2023 were included in the study. Approval from the Ethical Committee of Isfahan University of Medical Sciences was obtained prior to conducting this study. Results: We included 152 adult patients who completed the GOS-E and the QOLIBRI-OS three-month post-injury. The median age was 35 years (IQR = 17-70). Most patients 139 (91.4%) were classified as having a severe TBI. Conclusion: The results of the present study showed that both the use of GCS and Rotterdam CT scores can be effective in predicting the three-month mortality and QOLIBRI-OS scores of patients, with the difference that the predictive power of the three-month Rotterdam CT score is greater than that of the GCS.

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OBJECTIVE: The aim of this study was to stratify poly-traumatic brain injury (poly-TBI) patterns into discrete classes and to determine the association of these classes with mortality and withdrawal of life-sustaining treatment (WLST). METHODS: The authors performed a single-center retrospective review of their institutional trauma registry from 2018 to 2020 to identify patients with traumatic brain injury (TBI). Patients were included if they had moderate to severe TBI, defined as Glasgow Coma Scale score ≤ 12 and Abbreviated Injury Scale (AIS) head score ≥ 3, and the presence of more than one TBI subtype. TBI subtypes were defined as subdural hemorrhage (SDH), subarachnoid hemorrhage (SAH), intracerebral hemorrhage (ICH), and epidural hemorrhage (EDH). Latent class analysis was used to identify patient classes based on TBI subtypes and Rotterdam CT (RCT) scores. The authors then evaluated class membership in relation to categorical outcomes of in-hospital mortality and WLST by using Lanza et al.'s method. RESULTS: A total of 125 patients met inclusion criteria for poly-TBI. Latent class analysis yielded 3 poly-TBI classes: class 1-mixed; class 2-SDH/SAH; and class 3-EDH/SAH. Class 1-mixed had a higher likelihood of SDH, SAH, and ICH, and a lower likelihood of EDH. Class 2-SDH/SAH had a higher likelihood of only SDH and SAH. Class 3-EDH/SAH had a higher likelihood of EDH and SAH, and a lower likelihood of SDH and ICH. Class 1-mixed was relatively more likely to have an RCT score of 2. Class 2-SDH/SAH was relatively more likely to have an RCT score of 2, 3, and 4. Class 3-EDH/SAH had a higher likelihood of an RCT score of 3, 4, and 5. Class 1-mixed had significantly lower mortality (χ2 = 7.968; p = 0.005) and less WLST (χ2 = 4.618; p = 0.032) than Class 2-SDH/SAH. Class 2-SDH/SAH had the highest probability of death (0.612), followed by class 3-EDH/SAH (0.385) and class 1-mixed (0.277). Similarly, class 2-SDH/SAH had the highest WLST probability (0.498), followed by class 3-EDH/SAH (0.615) and class 1-mixed (0.238). CONCLUSIONS: Distinct poly-TBI classes were associated with increased in-hospital mortality and WLST. Further research with larger datasets will allow for more comprehensive poly-TBI class definitions and outcomes analysis.

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BACKGROUND: Early ischemic changes on baseline imaging are commonly evaluated for acute stroke decision-making and prognostication. AIMS: We assess the association of early ischemic changes on clinical outcomes and whether it differs between intravenous tenecteplase and Alteplase. METHODS: Data are from the phase 3, Alteplase compared to Tenecteplase (AcT) trial. Subjects with anterior circulation stroke were included. Early ischemic changes were assessed using the Alberta Stroke Program Early CT score (ASPECTS). Efficacy outcomes included modified Rankin scale (mRS) 0-1, mRS 0-2, and ordinal mRS at 90 days. Safety outcomes included 24-h symptomatic intracerebral hemorrhage (sICH), any hemorrhage on follow-up scan, and 90-day mortality rate. Mixed-effects logistic regression was used to assess the association of ASPECTS (continuous and categorical (0-4 vs 5-7 vs 8-10)) with outcomes and if these associations were modified by thrombolytic type after adjusting for age, sex, and baseline stroke severity. RESULTS: Of the 1577 patients in the trial, 901 patients (56.3%; median age 75 years (IQR 65-84), 50.8% females, median National Institute of Health Stroke Scale (NIHSS) 14 (IQR 17-19)) with anterior circulation stroke were included. mRS 0-1 at 90 days was achieved in 1/14 (0.3%), 43/160 (14.7%), and 252/726 (85.1%) in the ASPECTS 0-4, 5-7, and 8-10 groups respectively. Every one-point decrease in ASPECTS was associated with 2.7% and 1.9% decrease in chances of mRS 0-1 and mRS 0-2 at 90 days, respectively, and 1.9% chances of increase in mortality at 90 days. Subgroup analysis in endovascular thrombectomy (EVT)-treated population showed similar results. Thrombolytic type did not modify this association between ASPECTS and 90-day mRS 0-1 (P-interaction 0.75). There was no significant interaction by thrombolytic type with any other outcomes. CONCLUSION: Similar to prior studies, we found that every one-point decrease in ASPECTS was associated with poorer clinical and safety outcomes. This effect did not differ between alteplase and tenecteplase. DATA ACCESS STATEMENT: Data shall made available on reasonable request from the PI (BMM).

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In cystic lung diseases such as lymphangioleiomyomatosis (LAM), a CT-based cyst score that measures the percentage of the lung volume occupied by cysts is a common index of the cyst burden in the lungs. Although the current semi-automatic measurement of the cyst score is well established, it is susceptible to human operator variabilities. We recently developed a fully automatic method incorporating adaptive features in place of manual adjustments. In this clinical study, the automatic method is validated against the standard method in several aspects. These include the agreement between the cyst scores of the two methods, the agreement of each method with independent tests of pulmonary function, and the temporal consistency of the measurements in the consecutive visits of the same patients. We found that the automatic method agreed with the standard method as well as the agreement between two trained operators running the same standard method; both methods obtained the same level of correlation with laboratory pulmonary function tests; the automated method had better temporal consistency than the standard method (p < 0.0001). The study indicates that the automatic method could replace the standard method and provide better consistency in assessing the extent of cystic changes in the lungs of patients.

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Background: The extent of ischemic injury in acute stroke is assessed in clinical practice using the Acute Stroke Prognosis Early CT Score (ASPECTS) rating system. However, current ASPECTS semi-quantitative topographic scales assess only the middle cerebral artery (MCA) (original ASPECTS) and posterior cerebral (PC-ASPECTS) territories. For treatment decision-making in patients with anterior cerebral artery (ACA) occlusions and internal carotid artery (ICA) occlusions with large ischemic cores, measures of all hemispheric regions are desirable. Methods: In this cohort study, anatomic rating systems were developed for the anterior cerebral (AC-ASPECTS, 3 points) and anterior choroidal artery (ACh-ASPECTS, 1 point) territories. In addition, a total supratentorial hemisphere (H-ASPECTS, 16 points) score was calculated as the sum of the MCA ASPECTS (10 regions), supratentorial PC-ASPECTS (2 regions), AC-ASPECTS (3 regions), and ACh-ASPECTS (1 region). Three raters applied these scales to initial and 24 h CT and MR images in consecutive patients with ischemic stroke (IS) due to ICA, M1-MCA, and ACA occlusions. Results: Imaging ratings were obtained for 96 scans in 50 consecutive patients with age 74.8 (±14.0), 60% female, NIHSS 15.5 (9.25-20), and occlusion locations ICA 34%; M1-MCA 58%; and ACA 8%. Treatments included endovascular thrombectomy +/- thrombolysis in 72%, thrombolysis alone in 8%, and hemicraniectomy in 4%. Among experienced clinicians, inter-rater reliability for AC-, ACh-, and H-ASPECTS scores was substantial (kappa values 0.61-0.80). AC-ASPECTS abnormality was present in 14% of patients, and ACh-ASPECTS abnormality in 2%. Among patients with ACA and ICA occlusions, H-ASPECTS scores compared with original ASPECTS scores were more strongly associated with disability level at discharge, ambulatory status at discharge, discharge destination, and combined inpatient mortality and hospice discharge. Conclusion: AC-ASPECTS, ACh-ASPECTS, and H-ASPECTS expand the scope of acute IS imaging scores and increase correlation with functional outcomes. This additional information may enhance prognostication and decision-making, including endovascular thrombectomy and hemicraniectomy.

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Background: Melioidosis pneumonia, caused by the bacterium Burkholderia pseudomallei, is a serious infectious disease prevalent in tropical regions. Chest computed tomography (CT) has emerged as a valuable tool for assessing the severity and progression of lung involvement in melioidosis pneumonia. However, there persists a need for the quantitative assessment of CT characteristics and staging methodologies to precisely anticipate disease progression. This study aimed to quantitatively extract CT features and evaluate a CT score-based staging system in predicting the progression of melioidosis pneumonia. Methods: This study included 97 patients with culture-confirmed melioidosis pneumonia who presented between January 2002 and December 2021. Lung segmentation and annotation of lesions (consolidation, nodules, and cavity) were used for feature extraction. The features, including the involved area, amount, and intensity, were extracted. The CT scores of the lesion features were defined by the feature importance weight and qualitative stage of melioidosis pneumonia. Gaussian process regression (GPR) was used to predict patients with severe or critical melioidosis pneumonia according to CT scores. Results: The melioidosis pneumonia stages included acute stage (0-7 days), subacute stage (8-28 days), and chronic stage (>28 days). In the acute stage, the CT scores of all patients ranged from 2.5 to 6.5. In the subacute stage, the CT scores for the severe and mild patients were 3.0-7.0 and 2.0-5.0, respectively. In the chronic stage, the CT score of the mild patients fluctuated approximately between 2.5 and 3.5 in a linear distribution. Consolidation was the most common type of lung lesion in those with melioidosis pneumonia. Between stages I and II, the percentage of severe scans with nodules dropped from 72.22% to 47.62% (P<0.05), and the percentage of severe scans with cavities significantly increased from 16.67% to 57.14% (P<0.05). The GPR optimization function yielded area under the receiver operating characteristic curves of 0.71 for stage I, 0.92 for stage II, and 0.87 for all stages. Conclusions: In patients with melioidosis pneumonia, it is reasonable to divide the period (the whole progression of melioidosis pneumonia) into three stages to determine the prognosis.

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BACKGROUND: As the effects of immunosuppression are not still clear on COVID-19 patients, we conducted this study to identify clinical and laboratory findings associated with pulmonary involvement in both immunocompromised and immunocompetent patients. METHODS: A case-control of 107 immunocompromised and 107 immunocompetent COVID-19 patients matched for age and sex with either positive RT-PCR or clinical-radiological findings suggestive of COVID-19 enrolled in the study. Their initial clinical features, laboratory findings, chest CT scans, and short-term outcomes (hospitalization time and intensive care unit [ICU] admission) were recorded. In addition, pulmonary involvement was assessed with the semi-quantitative scoring system (0-25). RESULTS: Pulmonary involvement was significantly lower in immunocompromised patients in contrast to immunocompetent patients, especially in RLL (p = 0.001), LUL (p = 0.023), and both central and peripheral (p = 0.002), and peribronchovascular (p = 0.004) sites of lungs. Patchy (p < 0.001), wedged (p = 0.002), confluent (p = 0.002) lesions, and ground glass with consolidation pattern (p < 0.001) were significantly higher among immunocompetent patients. Initial signs and symptoms of immunocompromised patients including dyspnea (p = 0.008) and hemoptysis (p = 0.036), respiratory rate of over 25 (p < 0.001), and spo2 of below 93% (p = 0.01) were associated with higher pulmonary involvement. Total chest CT score was also associated with longer hospitalization (p = 0.016) and ICU admission (p = 0.04) among immunocompromised patients. CONCLUSIONS: Pulmonary involvement score was not significantly different among immunocompromised and immunocompetent patients. Initial clinical findings (dyspnea, hemoptysis, higher RR, and lower Spo2) of immunocompromised patients could better predict pulmonary involvement than laboratory findings.

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Objective: The aim of this study is to investigate the relationship between the volume of specific regional infarction and the prognosis of patients who undergo mechanical thrombectomy (MT) for acute large vessel occlusion. Methods: In this study, we collected the clinical and imaging features of patients with unilateral acute anterior circulation ischemic stroke from January 2021 to June 2023 in the Second Affiliated Hospital of Nanchang University. All patients underwent CT perfusion and non-contrast CT scan before MT. The ASPECTS was assessed based on imaging data, and artificial intelligence was used to obtain the percentage of infarction in each of the 10 regions of ASPECTS. According to the modified Rankin Scale, the patients were divided into the good prognosis group and poor prognosis group at the 90-day follow-up. Various indicators in the two groups were compared. Multivariable logistic regression was used to assess the risk factors for poor prognosis. The relationship between core infarction volume and the probability of poor prognosis was plotted to analyze the trend of poor prognosis with changes in the proportion of infarction volume. Finally, a receiver operating characteristic curve was constructed to analyze the predictive ability on poor prognosis. Results: A total of 91 patients were included, with 58 patients having a good prognosis (mRS ≤ 2) and 33 patients having a poor prognosis (mRS ≥ 3). Multivariate analysis showed that NIHSS score and core infarction involving the internal capsule and M6 region were independent risk factors for poor prognosis. According to the linear correlation, a higher ratio of core infarction volume in the internal capsule or M6 region was linked to an increased risk of a poor prognosis. However, the non-linear analysis revealed that the prognostic impact of core infarction volume was significant when the ratio was greater than 69.7%. The ROC curve indicated that the combination of NIHSS score, infarct location, and the ratio of infarct volume has an AUC of 0.87, with a sensitivity of 84.8% and a specificity of 84.5%. Conclusion: It is important to examine the location and volume of the infarct in the internal capsule and M6 when deciding whether to do a MT.

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Rationale and objectives: The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors. Materials and methods: This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination. Results: A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed. Conclusion: The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.

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BACKGROUND: Chronic rhinosinusitis (CRS) is one of the most common health disorders in humans and has a major impact on health-related quality of life (HRQoL). Of the many factors contributing to the etiology of CRS, less is known about the correlation between CRS and bacterial biofilms and their impact on HRQoL. OBJECTIVE: The aim of this prospective study was to investigate the relationship between biofilm-producing bacteria and patients' objective findings and HRQoL. METHODS: Forty-eight patients with CRSwNP were enrolled in a 12-month prospective study. The Lund-Mackay (LM) CT and endoscopic Lund-Kennedy (LK) scores were obtained before endoscopic sinus surgery (ESS), and patients completed the HRQoL instruments: the 22-item Sinonasal Outcome Test (SNOT-22), the 36-item Short Questionnaire (SF-36), and the visual analog scale (VAS). A sinus culture was obtained at ESS, bacteria were isolated, and in vitro quantification of the biofilm was performed. The LK score and HRQoL were determined postoperatively at months 1, 3, 6, and 12. RESULTS: The most common bacterial isolates in patients with CRSwNP were Staphylococcus aureus (28%), coagulase-negative staphylococci (52%), and Pseudomonas aeruginosa (8%). Preoperatively, the highest LM and LK scores were found in patients with strong biofilm producers. Postoperative LK scores were significantly reduced in all patients. Postoperative VAS scores were significantly reduced from month 1 to month 12 postoperatively. Patients with strong biofilm producers had significantly worse nasal blockage, secretion, headache, facial pressure and pain, and loss of smell preoperatively, compared to patients with low biofilm producers. The most significant reduction in preoperative scores SNOT-22 and SF-36 (excluding physical functioning) was seen in patients with S. aureus and P. aeruginosa. CONCLUSIONS: Patients with strong biofilm producers had higher LK and LM scores preoperatively, and greater improvement in LK and HRQoL scores postoperatively. Microbiologic surveillance of all CRS patients is recommended.

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This study aimed to evaluate the safety and efficacy of intra-arterial (IA) administration of low- dose tirofiban during endovascular therapy in patients with large ischemic core volumes on initial brain CT. Patients were divided into two groups based on the use of IA tirofiban. We identified 87 patients (16 and 71 patients in the tirofiban and no-tirofiban groups, respectively) with acute ischemic stroke due to intracranial artery occlusion who underwent endovascular therapy with a low Alberta Stroke Program Early CT scores (2-5). Multivariate logistic regression analysis revealed no association between IA tirofiban administration and serious postprocedural hemorrhagic complications (adjusted odds ratio (aOR), 0.720; 95% confidence interval (CI) 0.099-5.219; p = 0.960), any radiologic hemorrhage (aOR 0.076; 95% CI 0.003-2.323; p = 0.139), or 3-month mortality (aOR, 0.087; 95% CI 0.005-1.501; p = 0.093). However, IA tirofiban was associated with a lower 90-day mRS score (aOR, 0.197; 95% CI 0.015-1.306; p = 0.017) and change of NIHSS compared with baseline (aOR, 0.698; 95% CI 0.531-0.917; p = 0.010). IA tirofiban administration during endovascular therapy in patients with large ischemic core volumes may be effective and safe.

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Objective: Differentiating 2 types of chronic rhinosinusitis with nasal polyps (CRSwNP) is important for the treatment. The current diagnostic methods using single indicators, including peripheral blood eosinophils and traditional sinus computed tomography (CT) scores, are not accurate. In this study, we aimed to investigate the diagnostic value of combining peripheral blood eosinophils and improved sinus CT scores for eosinophic chronic rhinosinusitis (ECRS). Study Design: Retrospective cohort. Setting: Tertiary medical center. Methods: We conducted a study involving 81 patients with CRSwNP. Peripheral blood samples were collected from the non-ECRS and ECRS groups. Improved three-dimensional volume image analysis and Lund-Mackay scoring system were performed to quantify the thickening of sinus mucosa. Multivariate binary logistic regression analysis was carried out to detect the predictive value of the scoring indicators. For significant indexes, receiver operating characteristic (ROC) curve analysis was applied. Results: The ECRS group had higher levels of blood eosinophil percentage and count, ethmoid sinus score, total sinus score, the ratio of ethmoid sinus score and maxillary sinus score, and the difference between ethmoid and maxillary score, compared to the non-ECRS group (P < 0.05). Binary logistic regression analysis demonstrated that both blood eosinophil percentage and the improved E - M score (subtraction of ethmoid and maxillary sinus scores) were significant predictors of ECRS diagnosis (P < .01). ROC curve analysis indicated that the combination of improved E - M score and blood eosinophil percentage had a higher diagnostic value compared to either factor alone (area under the curve = 0.874). Conclusion: Our study suggested the combination of improved total ethmoid sinus-maxillary score and blood eosinophil percentage is more accurate in predicting the diagnosis of ECRS.

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Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.

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BACKGROUND: Alberta stroke program early CT score (ASPECTS) is a semi-quantitative evaluation method used to evaluate early ischemic changes in patients with acute ischemic stroke, which can guide physicians in treatment decisions and prognostic judgments. OBJECTIVE: We propose a method combining deep learning and radiomics to alleviate the problem of large inter-observer variance in ASPECTS faced by physicians and assist them to improve the accuracy and comprehensiveness of the ASPECTS. METHODS: Our study used a brain region segmentation method based on an improved encoding-decoding network. Through the deep convolutional neural network, 10 regions defined for ASPECTS will be obtained. Then, we used Pyradiomics to extract features associated with cerebral infarction and select those significantly associated with stroke to train machine learning classifiers to determine the presence of cerebral infarction in each scored brain region. RESULTS: The experimental results show that the Dice coefficient for brain region segmentation reaches 0.79. Three radioactive features are selected to identify cerebral infarction in brain regions, and the 5-fold cross-validation experiment proves that these 3 features are reliable. The classifier trained based on 3 features reaches prediction performance of AUC = 0.95. Moreover, the intraclass correlation coefficient of ASPECTS between those obtained by the automated ASPECTS method and physicians is 0.86 (95% confidence interval, 0.56-0.96). CONCLUSIONS: This study demonstrates advantages of using a deep learning network to replace the traditional template registration for brain region segmentation, which can determine the shape and location of each brain region more precisely. In addition, a new brain region classifier based on radiomics features has potential to assist physicians in clinical stroke detection and improve the consistency of ASPECTS.

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Objective To investigate the characteristics of blood routine,chest computed tomography(CT)imaging and short-term evolution of hemodialysis patients infected with Omicron variant of severe acute respiratory syndrom coronavirus 2(SARS-CoV-2).Methods A total of 204 patients diagnosed with Omicron variant infection in the First Hospital of Hohhot from September 2022 to September 2023 were retrospectively reviewed.Among them,89 patients with end-stage renal disease(ESRD)who were receiving hemodialysis were included in the hemo-dialysis group.The remaining 115 patients were control group,and the first blood routine results chest com-puted tomography(CT)imaging data were observed.Thirty-four patients in the hemodialysis group and 29 patients in the control group had complete pulmonary CT imaging data on the day of admission,5-6 days and 10-12 days after admission.The characteristics and chest CT scores of all cases were analyzed.Results 1)The percentage of monocytes,neutrophils,neutrophil/lymphocyte ratio and chest CT score of the hemo-dialysis group were higher than those of the control group,while the white blood cells,lymphocytes and lymphocyte percentage were lower than those of the control group.2)The positive rate of first chest CT was 49.4%in hemo-dialysis group and 35.7%in control group.3)The chest CT scores of the hemo-dialysis group and the control group on day 5 and day 6 were higher than those of first check.Chest CT was reexamined on days 10-12,and scores were higher in the hemo-dial-ysis group than in the control group.Conclusions Hemo-dialysis patients with COVID-19 have higher blood routine indexes,higher positive rate of lung CT and slower absorption than non-hemodialysis patients.

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Background: von Willebrand factor (VWF) has been widely recognized as a biomarker for endothelial cell activation in trauma and inflammation. Traumatic brain injury (TBI) is characterized by cerebral vascular injury and subsequent inflammation. The objective of this study was to investigate the correlation between VWF levels and clinical severity, as well as imaging abnormalities, in TBI patients. Additionally, the predictive value of VWF for patient outcomes was assessed. Methods: We conducted a prospective study to recruit acute TBI patients who were admitted to the emergency department within 24 h. Healthy individuals from the medical examination center were recruited as the control group. This study aimed to compare the accuracy of VWF in discriminating TBI severity and imaging abnormalities with the Glasgow Coma Scale (GCS) and Rotterdam computed tomography (CT) scores. We also analyzed the predictive value of these outcomes using the Glasgow Outcome Scale (GOS) and 6-month mortality. Results: The plasma concentration of VWF in TBI patients (84.7 ± 29.7 ng/ml) was significantly higher than in healthy individuals (40 ± 8.8 ng/ml). There was a negative correlation between VWF levels and GCS scores, as well as a positive correlation between VWF levels and Rotterdam CT scores. The area under the curve (AUC) for VWF in discriminating mild TBI was 0.76 (95% CI: 0.64, 0.88), and for predicting negative CT findings, it was 0.82 (95% CI: 0.72, 0.92). Meanwhile, the AUC of VWF in predicting mortality within 6 months was 0.70 (95% CI: 0.56, 0.84), and for a GOS score lower 4, it was 0.78 (95% CI: 0.67, 0.88). Combining VWF with either the GCS or Rotterdam CT score improved the prediction ability compared to using VWF alone. Conclusion: VWF levels were significantly elevated in patients with TBI compared with healthy individuals. Furthermore, VWF levels demonstrated a negative correlation with GCS scores and a positive correlation with Rotterdam CT scores. In terms of predicting mortality, VWF alone was not sufficient, but its predictive power was enhanced when combined with either the Rotterdam CT score or GCS. These findings suggest that VWF may serve as a potential biomarker for assessing the severity and prognosis of TBI patients.

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BACKGROUND: It has been reported that mid-regional proadrenomedullin (MR-proADM) could be considered a useful tool to stratify the mortality risk in COVID-19 patients upon admission to the emergency department (ED). During the COVID-19 outbreak, computed tomography (CT) scans were widely used for their excellent sensitivity in diagnosing pneumonia associated with SARS-CoV-2 infection. However, the possible role of CT score in the risk stratification of COVID-19 patients upon admission to the ED is still unclear. AIM: The main objective of this study was to assess if the association of the CT findings alone or together with MR-proADM results could ameliorate the prediction of in-hospital mortality of COVID-19 patients at the triage. Moreover, the hypothesis that CT score and MR-proADM levels together could play a key role in predicting the correct clinical setting for these patients was also evaluated. METHODS: Epidemiological, demographic, clinical, laboratory, and outcome data were assessed and analyzed from 265 consecutive patients admitted to the triage of the ED with a SARS-CoV-2 infection. RESULTS AND CONCLUSIONS: The accuracy results by AUROC analysis and statistical analysis demonstrated that CT score is particularly effective, when utilized together with the MR-proADM level, in the risk stratification of COVID-19 patients admitted to the ED, thus helping the decision-making process of emergency physicians and optimizing the hospital resources.

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Objective Head trauma of any severity, including concussions and skull fractures, can cause a traumatic brain injury (TBI). Prognostication plays a vital role in the scenario of urgency put forth by TBI. The application of CT-based scoring systems developed by the Rotterdam CT score and Marshall classification system appears to be appropriate for the early and precise prediction of clinical outcomes in TBI patients. The present study was designed to determine the predictive value of the Rotterdam CT score and Marshall classification system for in-hospital mortality in patients with TBI. Methods All adult patients (≥ 18 years) with acute traumatic brain injury presented over a period from February 2019 to November 2022 were included. Only those patients who had undergone a plain CT scan of the brain during the initial presentation at the emergency department (ED) were considered. Patients who presented with penetrating brain injury as well as those who died on arrival or who died prior to the initial CT scan of the brain were excluded. A total of 127 patients were included in the final data analysis. Based on initial CT-scan findings, the Rotterdam CT score and Marshall classification system were calculated in order to predict in-hospital mortality. Results The study was dominated by male patients (85.8%) as compared to female patients (14.2%). The overall mortality rate was 32.3% (n = 41). The mortality rate among males and females was 30.3% (33/109) and 44.4% (8/18), respectively. As per the Glasgow Coma Scale (GCS) classification, the severity of the injury was mild in 12.6% of the study subjects, moderate in 22%, and severe in 65.4%. The mortality rate among the patients with mild severity was 12.5% (2/16), while it was 28.6% in moderate (8/28) and 37.3% (31/83) in the severe category group. The best cut-off point of the Rotterdam score for predicting mortality was >4 (as per the Youden Index), which had a sensitivity and specificity of 60.98% and 90.70%, respectively, while the cut-off point of the Marshall CT classification for predicting mortality was >3 (as per the Youden Index), which had a sensitivity of 82.93% and a specificity of 75.58%. There was only a minor difference in the area under the curve (AUC) value of the receiver operating characteristic curve (ROC) curve between the Rotterdam CT score (0.827) and the Marshall classification system (0.833). Conclusion The Rotterdam and Marshall CT scores have demonstrated significant independent prognostic value and may serve as a useful initial evaluation tool for risk stratification of in-hospital mortality among patients with TBI.

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Detecting the early signs of stroke using non-contrast computerized tomography (NCCT) is essential for the diagnosis of acute ischemic stroke (AIS). However, the hypoattenuation in NCCT is difficult to precisely identify, and accurate assessments of the Alberta Stroke Program Early CT Score (ASPECTS) are usually time-consuming and require experienced neuroradiologists. To this end, this study proposes DGA3-Net, a convolutional neural network (CNN)-based model for ASPECTS assessment via detecting early ischemic changes in ASPECTS regions. DGA3-Net is based on a novel parameter-efficient dihedral group CNN encoder to exploit the rotation and reflection symmetry of convolution kernels. The bounding volume of each ASPECTS region is extracted from the encoded feature, and an attention-guided slice aggregation module is used to aggregate features from all slices. An asymmetry-aware classifier is then used to predict stroke presence via comparison between ASPECTS regions from the left and right hemispheres. Pre-treatment NCCTs of suspected AIS patients were collected retrospectively, which consists of a primary dataset (n = 170) and an external validation dataset (n = 90), with expert consensus ASPECTS readings as ground truth. DGA3-Net outperformed two expert neuroradiologists in regional stroke identification (F1 = 0.69) and ASPECTS evaluation (Cohen's weighted Kappa = 0.70). Our ablation study also validated the efficacy of the proposed model design. In addition, class-relevant areas highlighted by visualization techniques corresponded highly with various well-established qualitative imaging signs, further validating the learned representation. This study demonstrates the potential of deep learning techniques for timely and accurate AIS diagnosis from NCCT, which could substantially improve the quality of treatment for AIS patients.

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